光谱学与光谱分析, 2011, 31 (2): 390, 网络出版: 2011-03-24  

近红外漫反射线性加和光谱在烟叶复烤配方中的应用

The Application of Near-Infrared Diffuse Reflection Spectra Based on the Principle of Linear Additive in Tobacco Redrying Formula
作者单位
1 中国农业大学信息与电气工程学院, 北京100083
2 玉溪红塔集团技术中心, 云南 玉溪653100
3 中国农业大学理学院, 北京100193
摘要
应用近红外光谱分析技术进行烟叶复烤配方的辅助分析以及设计过程中, 需要大量的不同混合比例的样品光谱, 而混合样品光谱在实际生产过程中是很难获得的; 且不同分级的样品很难实现均匀混合, 不可避免的引入误差。 文章提出了应用近红外漫反射光谱的线性加和原理产生“理论混合均匀光谱”来代替实际的混合样品光谱, 不仅能够消除混合不均匀造成的误差, 而且省去了制备混合样品和测试光谱的过程, 省时、 省力、 省原料。 从原光谱、 导数光谱、 主成分、 以及PPF投影四个方面进行了线性加和光谱与实测混合样品光谱之间的对比分析, 验证了线性加和光谱的可行性和优越性。
Abstract
In the process of analyzing and designing tobacco redrying formula using near infrared spectroscopy, a great deal of spectra for different ratio mixed samples are badly needed. However these sample spectra are very hard to obtain in the actual production process. Furthermore, for the samples of different grades it is difficult to achieve the goal of even mixing, in consequence of introducing inevitable errors. In order to solve the above problems, the present paper proposes to use “theory of even mixed spectrum” produced by linear additive near infrared spectroscopy in place of the spectra of actual mixed samples. This way can not only eliminate the errors caused by uneven mixture, but also leave out the course of mixing samples and measuring spectra and save time, effort, and material simultaneously. This article analyzes the comparison between linear additive spectra and the spectra of actual mixed samples from the following four aspects: original spectra, derivative spectra, principal components, and the data of PPF projection, accordingly verifing the feasibility and superiority of the linear additive spectra.

张雅娟, 马翔, 张晔晖, 米津锐, 许莉, 王毅, 温亚东, 赵龙莲, 李军会, 张录达. 近红外漫反射线性加和光谱在烟叶复烤配方中的应用[J]. 光谱学与光谱分析, 2011, 31(2): 390. ZHANG Ya-juan, MA Xiang, ZHANG Ye-hui, MI Jin-rui, XU Li, WANG Yi, WEN Ya-dong, ZHAO Long-lian, LI Jun-hui, ZHANG Lu-da. The Application of Near-Infrared Diffuse Reflection Spectra Based on the Principle of Linear Additive in Tobacco Redrying Formula[J]. Spectroscopy and Spectral Analysis, 2011, 31(2): 390.

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